docstr: Takes as input a batch of frames and transforms them
  by applying the frame transformation model.
  
  Arguments:
      frames: Input batch of frames on which prediction
      needs to be made
  
  Returns:
      Transformed frames
docstr_tok: ["Takes","as","input","a","batch","of","frames","and","transforms","them","by","applying","the","frame","transformation","model",".","Arguments",":","frames",":","Input","batch","of","frames","on","which","prediction","needs","to","be","made","Returns",":","Transformed","frames"]
code: def transform(self, frames: ArrayLike) -> ArrayLike:
      """
      Takes as input a batch of frames and transforms them
      by applying the frame transformation model.
  
      Arguments:
          frames: Input batch of frames on which prediction
          needs to be made
  
      Returns:
          Transformed frames
      """
  
file_path: evadb/evadb/functions/abstract/abstract_function.py
imports: from abc import ABCMeta, abstractmethod
  from typing import List, Union
  import pandas
  from numpy.typing import ArrayLike
label_desc: Use image node_id 1 for calling the AbstractTransformationFunction obj's underlying member method code with example usage: obj.transform(frames) without return types